图 书 馆开课单位--布里斯托尔大学
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1MINI: Mining Informative Non-redundant Itemsets[迷你：挖掘信息的非冗余项集]
Tijl De Bie(布里斯托尔大学) 迷你：挖掘信息的非冗余项集
热度：25
Tijl De Bie(布里斯托尔大学) 迷你：挖掘信息的非冗余项集
热度：25
2Bounding the k-family-wise error-rate using resampling methods[使用重新采样方法的k个家庭明智的错误率边界]
Tijl De Bie(布里斯托尔大学)
热度：35
Tijl De Bie(布里斯托尔大学)
热度：35
34Shape constraints and algorithms[形状约束与算法]
Arne Kovac(布里斯托尔大学) We consider several problems in the areas of nonparametric regression and image analysis under shape constraints. The task is always to produce simple...
热度：58
Arne Kovac(布里斯托尔大学) We consider several problems in the areas of nonparametric regression and image analysis under shape constraints. The task is always to produce simple...
热度：58
5Automating News Content Analysis: An Application to Gender Bias and Readability[自动化新闻内容分析：性别与拜厄斯的可读性]
Omar Ali(布里斯托尔大学) Automating News Content Analysis: An Application to Gender Bias and Readability
热度：29
Omar Ali(布里斯托尔大学) Automating News Content Analysis: An Application to Gender Bias and Readability
热度：29
6Patterns in sets of points: an overview[模式的点集:概述]
Tijl De Bie(布里斯托尔大学) 1 - "Patterns in sets of points: an overview" "We illustrate the importance of optimization principles in the search for interesting pa...
热度：50
Tijl De Bie(布里斯托尔大学) 1 - "Patterns in sets of points: an overview" "We illustrate the importance of optimization principles in the search for interesting pa...
热度：50
789Automating Quantitative Narrative Analysis of News Data [新闻数据的自动化定量叙事分析]
Saatviga Sudhahar(布里斯托尔大学) We present a working system for large scale quantitative narrative analysis (QNA) of news corpora, which includes various recent ideas from text minin...
热度：41
Saatviga Sudhahar(布里斯托尔大学) We present a working system for large scale quantitative narrative analysis (QNA) of news corpora, which includes various recent ideas from text minin...
热度：41
10Subgroup discovery and rule evaluation in ROC space[roc空间中的子群发现与规则求值]
Peter A. Flach, Nada Lavrač(布里斯托尔大学) Traditionally, machine learning has focussed on induction of classification and prediction rules. More recently, non-predictive or descriptive inducti...
热度：41
Peter A. Flach, Nada Lavrač(布里斯托尔大学) Traditionally, machine learning has focussed on induction of classification and prediction rules. More recently, non-predictive or descriptive inducti...
热度：41